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Postgres MCP Pro

by dblinick
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Python
Hybrid

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    • postgres-mcp-server

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    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A3.7/5.0

    Scored across 9 tools

    Disambiguation4/5

    Tools are mostly distinct with clear purposes. The main potential confusion is between analyze_workload_indexes and analyze_query_indexes, which both recommend indexes but differ by input source (workload vs. explicit query list). Other tools like list_schemas, list_objects, and get_object_details build a clear hierarchy.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in lowercase snake_case (e.g., explain_query, list_schemas, analyze_db_health). The verbs (explain, list, get, analyze) are appropriate for their actions and the naming is uniform throughout the set.

    Tool Count5/5

    With 9 tools, the server is well-scoped for PostgreSQL database analysis and optimization. Each tool covers a distinct aspect (schemas, objects, query plans, indexes, health, top queries, execution) without unnecessary bloat, fitting the typical ideal range.

    Completeness4/5

    The tool set provides strong coverage for common PostgreSQL diagnostic workflows: exploring schemas/objects, explaining queries, analyzing indexes, identifying top queries, and running health checks. Minor gaps include lack of direct table bloat analysis and no management tools (e.g., vacuum or reindex), but these are not core to the server's apparent read/analysis focus.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources